A New Citation Recommendation Strategy Based on Term Functions in Related Studies Section
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In the era of big scholarly data, researchers frequently encounter the following problems when writing scientific articles: 1) it's challenging to select appropriate references to support the research idea, and 2) literature review is not conducted extensively, which leads to working on a research problem that has been well addressed by others. Citation recommendation assists researchers to decide which article should be cited in a timely manner, as well as perform comprehensive and high-quality review of scientific literature. Some work has been done on this valuable and challenging task, but few of them focused on applying the semantic information of the citation context. This paper proposes a new citation recommendation strategy based on term function - the functions or roles of citation context in related studies section. We present 9 term functions as identified from the literature and annotated 531 research papers in 3 areas to evaluate our approach. The experiment results demonstrate that term functions are effective to identifying valuable references. The proposed method recommends more accurate citations for a given topic when compared to several baseline methods. The citation recommendation strategy can be helpful to generate automatic summaries and literature reviews.
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